ObjectivesThe American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS) provides a standardized framework for thyroid nodule risk stratification based on predefined ultrasound features. This study aimed to evaluate the accuracy and robustness of ChatGPT-5.6 Sol in extracting and scoring ACR...
Zi-Man Chen, Ying-Li Wang· Journal of International Med...· 0 citations
BACKGROUND
Ultrasound (US) is widely used for assessing lymph node (LN) status, but its diagnostic accuracy remains highly operator dependent. A robust computer-assisted diagnostic model may enhance clinical performance and improve inter-operator and inter-center consistencies.
PURPOSE
To develop and validate a multi...
Xin-Yang Han, Jing-Guo Qu, Simon Takadiyi Gunda et al.· La Radiologia medica· 0 citations
Clinician-recorded structured ACR TI-RADS features improved ChatGPT-5.4 thyroid nodule classification accuracy when provided alongside ultrasound images, however, the combined strategy did not achieve higher overall accuracy than features-only input.
Publicly available multimodal LLMs showed measurable but heterogeneous performance in grayscale ultrasound-based thyroid nodule classification, but none of the models matched senior radiologist-level performance.
